AI-powered NMR compound identification for pharma R&D
Rombo AI accelerates compound identification by turning manual, expert-dependent interpretation into an assisted, scalable, and validable workflow for analytical chemistry teams.
Use case — Pharma R&D
Move from slow spectral interpretation to expert-assisted identification
Compound identification from NMR spectra is often a high-value bottleneck in discovery, impurity analysis, natural products, and metabolite characterization. Rombo AI helps teams reduce manual effort while keeping expert review at the center of the final decision.
The customer problem
Interpreting NMR spectra for unknown or partially known compounds can require days or weeks of expert work. The process is often manual, hard to scale, and difficult to reproduce consistently across teams and projects.
Expert bottlenecks
Senior analytical chemists spend significant time on repetitive interpretation and candidate comparison.
Slow turnaround
Identification cycles can delay discovery decisions, impurity investigations, and downstream validation.
Limited scalability
Manual workflows are difficult to apply consistently across larger compound libraries, sample sets, and project portfolios.
The Rombo AI solution
Rombo AI provides an expert-assisted workflow that supports spectrum ingestion, pattern identification, candidate generation, candidate ranking, and expert review. The goal is to help teams reach a reviewed shortlist faster while preserving scientific control and validation.
Spectrum ingestion
Organize NMR spectra and associated context into a structured workflow for review and comparison.
Pattern identification
Highlight spectral patterns that support candidate screening and reduce repetitive manual interpretation.
Candidate ranking
Generate and rank candidate structures with confidence scoring to focus expert attention on the most plausible options.
Expert review
Keep analytical chemists in control of final interpretation, validation, and project-specific decision making.
Expected impact
- Reduce identification turnaround from days or weeks toward about 1 hour as a PoC target.
- Lower manual effort for spectral interpretation and candidate comparison.
- Increase reproducibility across analysts, projects, and compound classes.
- Scale compound identification workflows without removing expert oversight.
- Create a clearer audit trail from spectrum to candidate shortlist and review outcome.
How it helps your team
- Discovery teams can accelerate structural hypotheses and downstream prioritization.
- Analytical chemistry teams can focus expert time on review and validation instead of repetitive screening.
- Impurity teams can move faster from unknown signals to candidate explanations.
- R&D leadership gains a more scalable and reproducible workflow for high-value analytical decisions.